文章来源 | 恒源云社区(一个专注 AI 行业的共享算力平台恒源智享云)
原文地址 | SpaCy
最近分享了社区大佬们的一些语言处理类的论文,干货满满!
戳👇 可查看,也许就有你需要的知识点哦~
恒源云 _ 语音识别与语义处理领域之 NAG 优化器
恒源云 _LLD: 内部数据指导的标签去噪方法【ACL 2022】
恒源云 _Y-Tuning: 通过对标签表征进行微调的深度学习新范式【ACL 2022】
恒源云 _[SimCSE]:对比学习,只需要 Dropout?
恒源云 _ 语音识别与语义处理领域之 [机器翻译] 21.7 mRASP2
今天呢,就给大家分享一下如何在恒源云 GPU 服务器上如何使用 spaCy。
相信很多小伙伴都知道,spaCy 是一个自然语言处理库,包括分词、词性标注、词干化、命名实体识别、名词短语提取等功能。
那如何安装呢?
# 安装 spaCy 3 For CUDA 11.2,根据镜像 CUDA 版本替换 [] 内版本
pip install spacy[cuda112]==3.0.6
# 安装 spaCy 2 For CUDA 11.2,根据镜像 CUDA 版本替换 [] 内版本
pip install spacy[cuda112]==2.3.5
# 通过 spacy 模块下载模型因为墙可能不可用,可通过下面 pip 安装方式安装
python -m spacy download en_core_web_sm
# 安装 3.0.0 en_core_web_sm
pip install https://mirror.ghproxy.com/https://github.com/explosion/spacy-models/releases/download/en_core_web_sm-3.0.0/en_core_web_sm-3.0.0-py3-none-any.whl --no-cache
# 安装 2.3.1 en_core_web_sm
pip install https://mirror.ghproxy.com/https://github.com/explosion/spacy-models/releases/download/en_core_web_sm-2.3.1/en_core_web_sm-2.3.1.tar.gz --no-cache
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安装之后又如何使用呢?
import spacy
# Load English tokenizer, tagger, parser and NER
nlp = spacy.load("en_core_web_sm")
# Process whole documents
text = ("When Sebastian Thrun started working on self-driving cars at "
"Google in 2007, few people outside of the company took him "
"seriously. “I can tell you very senior CEOs of major American "
"car companies would shake my hand and turn away because I wasn’t "
"worth talking to,” said Thrun, in an interview with Recode earlier "
"this week.")
doc = nlp(text)
# Analyze syntax
print("Noun phrases:", [chunk.text for chunk in doc.noun_chunks])
print("Verbs:", [token.lemma_ for token in doc if token.pos_ == "VERB"])
# Find named entities, phrases and concepts
for entity in doc.ents:
print(entity.text, entity.label_)
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以上就是今天所有的分享内容啦。对了,提前预祝大家元旦快乐呀~
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